BackendForge: leaderboard

BackendForge (Peking University, 2026) asks coding agents to build a complete Dockerized Python backend service from a written specification and an OpenAPI contract for 56 services rewritten from open-source applications, judged only through black-box HTTP tests. Task success rate in percent, where a task counts only when the service passes every item of the final test oracle, including reviewed tests added during oracle co-evolution; higher is better.

Metric: Task success rate (%; final oracle of 7,890 items including 640 reviewed co-evolved items; 56 contract-defined backend services rewritten from open-source applications; from a visible spec and OpenAPI contract the agent builds a Dockerized Python service, scored only through black-box HTTP pytest items; a task counts only when every item passes; one attempt per task in the same mini-SWE-style coding harness). Source: arxiv.org. Saturation forecast: Around February 2027. 14 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.5 (xHigh)28.57#49 (GPT-5.5)
2Claude Opus 4.7 (Max)17.86#79 (Claude Opus 4.7)
3Gemini 3.5 Flash5.36#101
4GLM-5.13.57#179
5DeepSeek V4 Pro (Max)3.57#188 (DeepSeek V4 Pro)
6Claude Sonnet 4.6 (Max)3.57#161 (Claude Sonnet 4.6)
7Kimi K2.61.79#178
8DeepSeek V4 Pro (High)1.79#188 (DeepSeek V4 Pro)
9MiniMax-M2.70#518
10DeepSeek V4 Flash (Max)0#258 (DeepSeek V4 Flash)
11DeepSeek V4 Flash (High)0#258 (DeepSeek V4 Flash)
12Hy3-preview (High)0#316 (Hy3-preview)
13Qwen 3.6 Plus (High)0#222 (Qwen 3.6 Plus)

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=backendforge · How It Works · Data refreshed daily, snapshot 2026-11-13.